Hi KNIME community,
I was checking out the various ML nodes and I wanted to see what differences changing the different parameters of the learner and partitioner node makes to the result. I made a workflow in which these parameters are defined, taken from the learner node as flow variables, and combined with the results from the predictor node. I can then read these to an Excel or CSV and then compare the results with different configs with less manual correction.
This worked fine when I was using a simple Partitioner node. But then I wanted to try it with cross-validation, and this approach would not work with the X-Partitioner X-Aggregator loop as I am taking the flow variables outside the loop. I assume I have to nest this loop with another loop (Generic Loop Start - Loop Variable nodes, maybe), but I am unable to figure out how to set this up.
So very basically, I want to take the parameters from the leaner and partitioner nodes outside the Cross Validation loop. Is it possible? Or is there a better approach to capture these parameters? I am attaching the workflow here.
Thanks!
Cross Validation Loop.knwf (1.2 MB)